MétaCan
Menu
Back to cohort
Record W4409594148 · doi:10.5539/hes.v15n2p307

Educational Intentions and Expectations: Transfer Student Experiences

2025· article· en· W4409594148 on OpenAlexvenueno aff
Sweety Law

Bibliographic record

VenueHigher Education Studies · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsnot available
FundersCalifornia State University, East Bay
KeywordsPsychologyMathematics educationLikert scaleHigher educationPedagogyDevelopmental psychologyPolitical science

Abstract

fetched live from OpenAlex

Higher education in general and state-funded institutions especially will need to assess what an undergraduate education means in a changed geo-political socio-economic environment. For business schools, employability and future careers are stated outcomes to define a quality business education. Recent empirical scholarship has indicated significant relationship among perceived employability, student satisfaction, and institutional reputation. In an increasingly competitive higher education landscape, government, institution, community, and employer perspectives on employability describe a compelling yet incomplete picture. Missing is the student perspective. By providing qualitative insights, our study may expand the understanding obtained from prior empirical studies on student satisfaction and expectations of their time in university. By involving current students and a recent graduate, the study presents a dynamic view of the student lived university experience and student expectations.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.006
Threshold uncertainty score0.020

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.010
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0060.003
Open science0.0010.006
Research integrity0.0020.004
Insufficient payload (model declined to judge)0.0030.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.066
GPT teacher head0.492
Teacher spread0.426 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueHigher Education StudiesSame topicHigher Education Learning PracticesFrench-language works237,207